findmycells_colab.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/Defense-Circuits-Lab/findmycells/blob/main/findmycells_colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "edQTK9o1-1eu"
   },
   "source": [
    "# **Welcome to findmycells on Google Colab!**\n",
    "\n",
    "Before running the first cell: make sure, you're using a GPU!\n",
    "Go to \"Runtime\" > \"Change runtime type\" and select \"GPU\" as hardware accelerator!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "iX7W4A_X7CzR",
    "outputId": "c85938f0-5a3c-43dd-b1ce-db82a92bfd32"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "\u001b[0mINFO: pip is looking at multiple versions of jsonschema[format-nongpl] to determine which version is compatible with other requirements. This could take a while.\n",
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      "\u001b[?25hBuilding wheels for collected packages: wget, efficientnet-pytorch, pretrainedmodels, asciitree\n",
      "  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for wget: filename=wget-3.2-py3-none-any.whl size=9657 sha256=3c930ec230551cebb0a3ed50e3f34b637e1b20ac798f105c4875c5510d018436\n",
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      "  Created wheel for efficientnet-pytorch: filename=efficientnet_pytorch-0.7.1-py3-none-any.whl size=16427 sha256=3da73da01dd12520134116d35ba0bdbdd66ce4c6cb15179729cc07d0849e5fec\n",
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      "  Building wheel for pretrainedmodels (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for pretrainedmodels: filename=pretrainedmodels-0.7.4-py3-none-any.whl size=60945 sha256=4129a05069f39db61ea1c79194c0bdf10605ae315f96aebbb1640be50047a93d\n",
      "  Stored in directory: /root/.cache/pip/wheels/35/cb/a5/8f534c60142835bfc889f9a482e4a67e0b817032d9c6883b64\n",
      "  Building wheel for asciitree (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Created wheel for asciitree: filename=asciitree-0.3.3-py3-none-any.whl size=5034 sha256=b2ec2fe1e9b1c1948758306ae4bac44e5ea54e32093af446dafe4610f8fd5518\n",
      "  Stored in directory: /root/.cache/pip/wheels/7f/4e/be/1171b40f43b918087657ec57cf3b81fa1a2e027d8755baa184\n",
      "Successfully built wget efficientnet-pytorch pretrainedmodels asciitree\n",
      "Installing collected packages: wget, safetensors, json5, asciitree, uri-template, rpds-py, roifile, rfc3986-validator, rfc3339-validator, requests, pyzmq, python-json-logger, overrides, numcodecs, munch, jupyterlab-widgets, jsonpointer, jedi, imageio, imagecodecs, fqdn, fastremap, fasteners, connected-components-3d, async-lru, zarr, referencing, jupyter-server-terminals, jupyter-client, huggingface-hub, czifile, arrow, jsonschema-specifications, isoduration, jsonschema, jupyter-events, jupyter-server, widgetsnbextension, notebook-shim, jupyterlab-server, jupyter-lsp, jupyterlab, ipywidgets, ipyfilechooser, timm, pretrainedmodels, efficientnet-pytorch, segmentation-models-pytorch, deepflash2, cellpose, findmycells\n",
      "  Attempting uninstall: requests\n",
      "    Found existing installation: requests 2.27.1\n",
      "    Uninstalling requests-2.27.1:\n",
      "      Successfully uninstalled requests-2.27.1\n",
      "  Attempting uninstall: pyzmq\n",
      "    Found existing installation: pyzmq 23.2.1\n",
      "    Uninstalling pyzmq-23.2.1:\n",
      "      Successfully uninstalled pyzmq-23.2.1\n",
      "  Attempting uninstall: jupyterlab-widgets\n",
      "    Found existing installation: jupyterlab-widgets 3.0.8\n",
      "    Uninstalling jupyterlab-widgets-3.0.8:\n",
      "      Successfully uninstalled jupyterlab-widgets-3.0.8\n",
      "  Attempting uninstall: imageio\n",
      "    Found existing installation: imageio 2.25.1\n",
      "    Uninstalling imageio-2.25.1:\n",
      "      Successfully uninstalled imageio-2.25.1\n",
      "  Attempting uninstall: jupyter-client\n",
      "    Found existing installation: jupyter-client 6.1.12\n",
      "    Uninstalling jupyter-client-6.1.12:\n",
      "      Successfully uninstalled jupyter-client-6.1.12\n",
      "  Attempting uninstall: jsonschema\n",
      "    Found existing installation: jsonschema 4.3.3\n",
      "    Uninstalling jsonschema-4.3.3:\n",
      "      Successfully uninstalled jsonschema-4.3.3\n",
      "  Attempting uninstall: jupyter-server\n",
      "    Found existing installation: jupyter-server 1.24.0\n",
      "    Uninstalling jupyter-server-1.24.0:\n",
      "      Successfully uninstalled jupyter-server-1.24.0\n",
      "  Attempting uninstall: widgetsnbextension\n",
      "    Found existing installation: widgetsnbextension 3.6.4\n",
      "    Uninstalling widgetsnbextension-3.6.4:\n",
      "      Successfully uninstalled widgetsnbextension-3.6.4\n",
      "  Attempting uninstall: ipywidgets\n",
      "    Found existing installation: ipywidgets 7.7.1\n",
      "    Uninstalling ipywidgets-7.7.1:\n",
      "      Successfully uninstalled ipywidgets-7.7.1\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "google-colab 1.0.0 requires requests==2.27.1, but you have requests 2.31.0 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed arrow-1.2.3 asciitree-0.3.3 async-lru-2.0.3 cellpose-2.2.2 connected-components-3d-3.12.1 czifile-2019.7.2 deepflash2-0.1.7 efficientnet-pytorch-0.7.1 fasteners-0.18 fastremap-1.13.5 findmycells-0.1.3 fqdn-1.5.1 huggingface-hub-0.16.4 imagecodecs-2023.7.10 imageio-2.21.3 ipyfilechooser-0.6.0 ipywidgets-7.6.5 isoduration-20.11.0 jedi-0.18.2 json5-0.9.14 jsonpointer-2.4 jsonschema-4.18.4 jsonschema-specifications-2023.7.1 jupyter-client-8.3.0 jupyter-events-0.6.3 jupyter-lsp-2.2.0 jupyter-server-2.7.0 jupyter-server-terminals-0.4.4 jupyterlab-4.0.3 jupyterlab-server-2.23.0 jupyterlab-widgets-1.0.2 munch-4.0.0 notebook-shim-0.2.3 numcodecs-0.11.0 overrides-7.3.1 pretrainedmodels-0.7.4 python-json-logger-2.0.7 pyzmq-25.1.0 referencing-0.30.0 requests-2.31.0 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 roifile-2023.5.12 rpds-py-0.9.2 safetensors-0.3.1 segmentation-models-pytorch-0.3.3 timm-0.9.2 uri-template-1.3.0 wget-3.2 widgetsnbextension-3.5.2 zarr-2.15.0\n"
     ]
    },
    {
     "data": {
      "application/vnd.colab-display-data+json": {
       "pip_warning": {
        "packages": [
         "zmq"
        ]
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pip install findmycells"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lXzo_as9AzTP"
   },
   "source": [
    "Restart the runtime after the cell above was executed!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qfbiIFntAO9f"
   },
   "source": [
    "The next step will ask you for authorization, to enable the programs you're running on Google colab to access your Google drive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "hlWsTmkI9FOQ",
    "outputId": "4002c1c8-842a-479f-c0b3-1a7bb27fa152"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mounted at /content/drive/\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "\n",
    "drive.mount(\"/content/drive/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8WKJEA1N_6Nt"
   },
   "source": [
    "If you're using findmycells on Colab for the first time and want to test our sample data, you have to execute the cell below.\n",
    "\n",
    "Make sure, you set the destination_dir to an existing directory!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "D_60lXj59fuJ"
   },
   "outputs": [],
   "source": [
    "from findmycells.utils import download_sample_data\n",
    "from pathlib import Path\n",
    "\n",
    "destination_dir = Path('/content/drive/My Drive/findmycells')\n",
    "\n",
    "download_sample_data(destination_dir_path = destination_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "xZGN-YKK7JXM"
   },
   "outputs": [],
   "source": [
    "from findmycells.interfaces import launch_gui"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 686,
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       "VBox(children=(HTML(value='<br><br><div style=\"font-size: 26px\" align=\"center\"><b>Welcome to <i>findmycells</i…"
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    "You can test, that findmycells can access the GPU by running the next cell:\n",
    "\n",
    "In case, it shows False, you probably missed, changing your runtime type."
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         "project_root_dir:\n",
         "│ \n",
         "└── microscopy_images:\n",
         "    │ \n",
         "    ├── wildtypes:\n",
         "    │   ├── week_01:\n",
         "    │   │   ├── mouse_01:\n",
         "    │   │   │   └── image_01.png\n",
         "    │   │   │   └── image_02.png\n",
         "    │   │   └── mouse_02:\n",
         "    │   │       └── image_01.png\n",
         "    │   │       └── image_02.png\n",
         "    │   │       └── image_04.png\n",
         "    │   └── week_04:\n",
         "    │       └── mouse_03:\n",
         "    │           └── image_08.png\n",
         "    │ \n",
         "    └── transgenics:\n",
         "        ├── week_01:\n",
         "        │   ├── mouse_04:\n",
         "        │   │   └── image_01.png\n",
         "        │   │   └── image_05.png\n",
         "        │   └── mouse_05:\n",
         "        │       └── image_01.png\n",
         "        │       └── image_02.png\n",
         "        └── week_04:\n",
         "            ├── mouse_06:\n",
         "            │   └── image_01.png\n",
         "            │   └── image_02.png\n",
         "            │   └── image_03.png\n",
         "            └── mouse_07:\n",
         "                └── image_01.png\n",
         "                └── image_08.png\n",
         "\n"
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